- Location
- Hyderabad
- Workplace
- Onsite
- Type
- Full-time
- Department
- Engineering
- Experience
- 5+ years
- Education
- Master
- Closing date
- Today
- Source
- CareersPage
Description
*MLOps Engineer* – 5 to 8+ years of experience,
Immediate Joiner / Notice Period up to 15 days
Work Mode: Onsite
Location: Hyderabad
*Position Title:* ML Ops Engineer
Role Summary:
Hilton Grand Vacations (HGV) is seeking a ML Ops Engineer to build and operate the platform, tooling, and automation that enable reliable delivery of machine learning solutions. This role is responsible for scalable pipelines, secure deployments, and monitoring to ensure models perform well in production and meet enterprise standards.
Work Hours and Location: Must be willing to work from the Hyderabad office on Eastern Standard Time Zone
Key Responsibilities:
ML Platform & Pipelines:
Design and implement end-to-end ML pipelines for training, validation, packaging, and deployment.
Create reusable templates and tooling for experimentation, feature consumption, and model lifecycle management.
CI/CD & Release Engineering:
Build CI/CD for ML (tests, quality gates, approvals) using Azure DevOps/GitHub Actions.
Manage model registry, artifact versioning, and environment reproducibility.
Deployment, Monitoring & Reliability:
Implement batch and real-time serving patterns; automate monitoring for drift, performance, and data quality.
Establish SLOs/SLAs for ML services; lead incident response and root-cause analysis for ML production issues.
Cloud & Security:
Operate ML infrastructure on Azure (preferred), including compute, networking, IAM, and secrets management.
Apply governance: access controls, auditability, and compliance requirements.
Technical Qualifications Needed:
Education:
Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related field.
Mandatory Required skills:
5–8+ years of experience in ML Ops, DevOps, Data Engineering. Data Science, or related roles.
Hands-on experience with Azure ML and/or Databricks, MLflow, and asset bundles.
Kubernetes and orchestration experience; familiarity with model serving frameworks.
Strong Python and SQL skills; experience with automated testing and observability.
Experience with monitoring/alerting (e.g., Azure Monitor, Prometheus/Grafana).
Desired Skills:
Infrastructure-as-Code (Terraform/Bicep) and policy-as-code experience.
Experience with feature stores and data quality frameworks.
Experience supporting regulated data environments and security reviews.
*Certifications*
Azure DevOps Engineer Expert, Azure Data Engineer Associate, or similar certifications preferred.
